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Chair of Statistics and Econometrics
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Business and Economic Forecasting (2026)

The teaching for this course will begin on April 21, 2026. 

Registration for the Lecture

Students have to sign in for this course in HISinOne. The registration in ILIAS will be carried out automatically.

Registration for the Exam

Please note that the registration for the lecture does not automatically mean that you are registered for the exam! A separate registration for the exam is mandatory!
You can find the current examination dates as well as further information on the registration for the examination as well as the deadlines for registration and deregistration of the examinations on the homepage of the examination office. 

Ilias

Access to the course in ILIAS is granted automatically after registration via HISinOne. Therefore, please ensure that you have registered in HISinOne. If necessary, admission to the ILIAS course can still be granted after a manual request to join in ILIAS.

Instructor

Alessandro Morico

Language

English

Lectures

Tuesdays from 12:15 to 13:45, HS 1221 KG I

Exercise Sessions

Thursdays from 14:15  to 15:45, HS 3042, KG III

Credits

6 ECTS

Work load

Approx. 180 hours

Requirements

Basic requirements:
Intermediate Econometrics
Sound knowledge of a programming language of choice (Matlab, R, Python, etc.)

Recommended requirements:
Financial Time Series Analysis

Qualification Target

This course equips students with state-of-the-art techniques for predicting future outcomes of business and economic phenomena with quantifiable certainty. Upon successful completion, participants will be able to not only implement and code forecasting models but also evaluate their performance on real-life datasets and compare them against competitors.

Contents

This course covers modern forecasting techniques with a balanced focus on econometric theory and empirical applications, and it is expected to make extensive use of statistical programming.


Course outline:

  1. Elements of forecasting
  2. Dynamic models: estimation, misspecification testing and forecasting
  3. Modelling and forecasting trends and seasonality in economics
  4. Forecasting under structural instability: static vs time-varying parameter models
  5. Ex-post evaluation (DM statistics, Mincer-Zarnowitz, etc.) and forecast combinations
  6. *Forecasting with many predictors I: diffusion indexes
  7. *Forecasting with many predictors II: Lasso and Ridge shrinkage
  8. *Model Confidence Set

*Time permitting

Main References

  • Diebold, F.X. (2001): Elements of forecasting (2nd Ed.), South Western/Thomson Learning.
  • Brockwell, P.J. & Davis, R.A. (2002): Introduction to time series and forecasting (2nd Ed), Springer.
  • Stock, J.H & Watson, M.W. (2020): Introduction to Econometrics (4th Ed), Pearson.
  • Pyndyck, R.S. & Rubinfeld, D.L. (1998): Econometric models and economic forecasts (4th Ed), McGraw-Hill.
  • Selected papers from the literature as additional material.

Exam

  • Please find further details on the examination office’s homepage.
  • In the exam you may use a non-programmable calculator, a hard copy of a German-English dictionary book and a one-sided A4 hand-written cheat sheet.

Exams and Exam Reviews

Grading

100% final exam

Target Group

  • M.Sc. VWL (Accounting, Finance and Taxation / Business Analytics / Constitutional Economics and Competition Policy / Empirical Economics / Network Economics and IT Risk Management)
  • M.Sc. BWL (Volkswirtschaftslehre / Quantitative Methoden / Wirtschaftsinformatik)
  • M.Sc. in Economics (Finance / Information Systems and Network Economics / Digital Markets)